ODNP is further complicated by the uncertainty in demands and available generation capacity. In [1]}, [2]}, [3]}, [4]}, [5]}, the load-generation uncertainty is addressed by constructing typical daily profiles, over which optimization is performed. However, the quality of solution obtained is not evaluated. The present work formulates a chance-constrained ODNP (cc-ODNP) to identify optimal microgrids in the planning stage. This is computationally challenging as the underlying deterministic formulation uses mixed integer linear program (MILP) and is not convex by nature. Hence, sampling and integer programming [6]} has been used to solve an approximation of the cc-ODNP, and the quality of the solution obtained is rigorously evaluated.
